The Shape of Work
The Shape of Work
#514: Sarbojit Mallick on the technological revolution in the recruitment sector
"Recruitment processes often inundate both recruiters and candidates, resulting in a substantial time-consuming effort. Our technology disrupts this conventional approach, leveraging data points from multiple sources to create candidate personas, aligning them with a company's ideal profile for a perfect match”
In today’s episode of The Shape Of Work podcast, Cue our enlightening conversation with Sarbojit Mallick, Co-Founder of Instahyre. With an extensive career spanning over a decade, he has contributed his expertise to diverse organizations such as Jindal Stainless Steel, Bristlecone, TripHippie, and GlobalShiksha. His academic journey includes a B.Tech degree from NIT Durgapur and an MBA earned from IIM Mumbai.
In this episode, we delve into the challenges that companies face when hiring and find unique insights into how Instahyre is solving these issues. Sarbojit paints a vivid picture of how technology can create a persona of both the candidate and the company to find the perfect fit.
Episode Highlights
- What are the main two problems faced by recruiters?
- Using AI to improve the recruitment process
- Describes problems in the job market where candidates are overwhelmed with irrelevant job opportunities
- Importance of leveraging technology and human interaction in the recruitment process
Follow Sarbojit on Linkedin
Produced by: Priya Bhatt
Podcast Host: Archit Sethi
About Springworks:
Springworks is a fully-distributed HR technology organisation building tools and products to simplify recruitment, onboarding, employee engagement, and retention. The product stack from Springworks includes:
SpringVerify— B2B verification platform
EngageWith— employee recognition and rewards platform that enriches company culture
Trivia — a suite of real-time, fun, and interactive games platforms for remote/hybrid team-building
SpringRole — verified professional-profile platform backed by blockchain, and
SpringRecruit — a forever-free applicant tracking system.
Springworks prides itself on being an organisation focused on employee well-being and workplace culture, leading to a 4.8 rating on Glassdoor for the 200+ employee strength company.
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Speaker 2:Hello and welcome to another episode of the Shape of Work podcast, and for this episode, we have with us Mr Sarboji Malik, who is the co-founder of InstaHire. Hi, sarboji, thank you for joining us. Hi, how are you doing? Doing great. Thank you for having us, thank you for coming here and joining us, and we look forward for a great session. So, to begin with, could you please take us through your career journey so far?
Speaker 3:So I am an engineering grad from NIT to Rukhapur and then I did my MBA from Niti Bombay right, not, I am Bombay and post that, I worked for some time couple of years and then I started my own company on travel. It was adventure travel and then, 2017, I was with InstaHire. We started off InstaHire and then right now, it has been completely on the recruitment side, and we first started off InstaHire with. The single most biggest pain point was that to solve candidate side issues and recruticide issues like recrotos are not getting good candidates, finding good candidates, but they are there in the market and candidates are not finding good jobs, which are there in the market. So that leads to a lot of frustration and a lot of miscommunication and stuff like that. So we developed our own tool.
Speaker 3:So Aditya the other co-founder, other founder and CEO, he developed the tool which was known as InstaMatch, which is the algorithm which helps to effortlessly find out data points about candidates and about companies and taking biggest historic data which is available on the internet and with our databases, and then match candidates with the perfect jobs so that candidates will not see relevant jobs and recruiters of companies will not see candidates which are not relevant for that job opening.
Speaker 3:So we keep both the sites happy and how. This is how we started off. We started off with only technology hiring tech hiring and right now we are into tech, non-tech and across domains like. We started off with product engineering, so only for companies like tech, companies like, say, google, walmart, amazon, and right now we are also into with banks, it services companies and also we work with recruitment consulting firms as in like they also use our tool. We are into expansion mode currently and we are expanding our team and expansion will be mostly into Indian subcontinent plus overseas, like Europe and US. So a brief about that is how we are trying to build InstaHire as of now.
Speaker 2:Awesome. So my next question is also very similar to what you said. I mean, how did the idea InstaHire originate? And also we would love to know the vision for the same.
Speaker 3:So Aditya was working on this idea from 2015 and he got some very good insights on how the recruitment industry actually operates. So on the recruiter side of it, we have seen problems like the recruiters post a job, find some certain keywords, and these are two ways we can do it they post a job and they see candidates, and they also do a search and with certain keywords and they find candidates. But the main issue was the systems were not intelligent enough to understand what kind of job it was, what kind of skills were actually required, and we'll throw you a bunch of data, thank you, which is, like, say, one to two percent relevant. That increases the time taken to hire one person and it definitely dents into the top line of a company, because if you take a lot of time to hire people and your projects get delayed and you cannot implement your GTM strategies properly. On the candidate side, if you have proper training and if you have inclination towards, say, python programming, but your background is different, you will start getting jobs which are not relevant. You will get calls which might not be relevant. That is one more issue which leads to a lot of frustration amongst our candidates. On the recruiter side, we have seen two problems, okay. First is then the cost of hiring was very high because you cannot use tools and then you have to rely on certain consulting firms, which increases the cost of your hiring. Number two if you spend a lot of time on these tools, you might not get the relevant results. That is one fear amongst the recruiters. These two problems we were solving we are still solving now with our advanced technology, but mostly we have solved a bunch of related problems associated with the two main problems which I have already told you.
Speaker 3:Our vision is to create a tool which is intelligent enough, using things like AI, ml, nlp and other technologies, so that whenever you post a job, the system understands what you are hiring for without any bias, and you get candidates which are relevant for you. On the other side also, relevant jobs are being shown to candidates so they don't get frustrated and they apply to only the jobs which they want to, so that they get their dream jobs. And on the other side, recruiters can build good teams to increase their throughput. That was the vision Right now we are launching. We have launched weekend drives or mass hiring drives, using the same technology and working wonders for very large tech companies which we work with.
Speaker 3:As I told you earlier, we have launched internships, which has been very, very useful for freshers and people who are in still in college, and also companies who hire a lot of freshers and college students for their internship work. We have also launched our own application tracking system, which is the ATS, which is being taken very well by the community. We work with around 11,000 plus enterprises companies, startups, smes. We have around our own database of candidates, which around 25 to 30 million candidates which are actively looking out, and then their passive candidates also, which is almost equal to the number of active candidates. So this is how which we look at we are, as I told you, we are expanding in India and also in the regions across, like South East Asia and US and Europe.
Speaker 2:I mean it's definitely like. I mean we all must have faced all these problems somewhere. Being on the either side of the table, whether we are employers or employees seeking jobs, we do get across such problems and Insta has definitely has been doing some great work to provide a solution to it. And definitely, with internships and everything, and with Insta is horizon being broadened with time, I definitely do hope that it will become one of those platforms of one stop solution for all when it comes to. So, talking about more, talking more about Insta higher. So could you elaborate on the key features that make Insta higher stand out in the edge of the landscape and what are the advantages that it offers over traditional recruitment methodologies?
Speaker 3:So as a traditional recruitment methodology. So I will give you an example. So suppose you're hiring for a role, say in Java ticket, and what you do is basically go to any of any tool and just go to search Java and skill and you get all the candidates. Then the recruiters normally messages or emails all these candidates. The thing is like if the keyword search takes up anything which is related to that OK on your resume and it will email all the candidates. So if you suppose you send one 10,000 emails to candidates, it might be the case that there is only one to two percent were relevant candidates and the rest 98% will not be relevant for your company, either on skill basis or on the positions they are currently working on. But these candidates they will. Some of the candidates will apply and you will find out that most of them are not relevant. So there is a time taken by this process. This process is a huge process which like sending emails and like reading through resumes, passing through resumes, finding relevant candidates. So this is done manually, was done manually. Ok, that we have used technology to do it, using our Instamatch algorithm.
Speaker 3:Number two is when, when companies come in, they want to hire, say, different person. So suppose, if a large company is hiring, they will hire people who are much, say, have worked in very large architecture, in a grand setting. These people, these candidates, will have a different mindset when a startup is hiring, they will hire people who have built something or are very comfortable working in scrappy environment Because, as you know, startups, like they, work majorly in very scrappy environment. So this kind of people, this kind of folks, where we, you, how will you differentiate this kind of people? So, but if you may, wise, they might look the same and they will have similar skills.
Speaker 3:But if you show candidates at a to companies like large companies, which candidates who are ready to, willing to work in startups and have always worked between startups, they will not apply to large companies mostly, and large companies will also not be very keen on taking this kind of candidates who have no experience in, say, very large and architecture or kind of very process oriented approach.
Speaker 3:So this is how you identify, how will identify this. So our technology they scrape some, like they get some data points from different aspects of a candidate profile on the social profiles, plus from their deposit trees, plus from the resume, plus what they actually write on the portal, on our portal. So they create a persona and then they create a persona of the company, so the company might be hiring this kind of candidates, a Java candidates, for the last 10 years okay, or five years. So we can see all the candidates which they have hired in the last 10 years or five years down the line and we can make make out key. This is the personality of the candidate which they actually want and they are working currently, who might be employees currently or might have left this company and working for the companies.
Speaker 3:So then, when you match this persona, you will get a perfect fit, and that is how we are trying to solve it. So this is not done by any traditional method. Traditional method is very, very simple. So you do a search, you find your candidates, you email them and then you like, spray them with emails and you pray so they come back and you get relevant profiles. That is how it actually should work, because it takes up a lot of bandwidth on both sides.
Speaker 3:The candidate will also look through emails, they will apply for the job, they will wait, they will not get a reply back maybe, and on the other hand, the recruiter is also overloaded with the applications which they have to see one by one and they might miss out on something. They might not get time to send back communication. This creates a lot of bad blood and a lot of issues around the brand because this brand doesn't reply to candidates and people will say like that. So this problem was also solved using our technology where recruiters will only see relevant candidates. They will only talk to relevant candidates, email them. 80 percent of the job of a recruiter is gone because they only see a bunch of candidates or pool of candidates which are relevant and they will only talk to them, give them better experience, can it experience, can it delight, and the candidate will also have a better understanding of the company and have jobs which actually he or she might be relevant and can crack. So that is how we are trying to solve it.
Speaker 3:Traditional methods as of now have not been able to do it. Our first aim was to. When we started off, we had a few companies which are using this product. Right now, most of the companies in the technology and also in the banking and services world user product and that has been the same thing which stuck like on the last six, seven years they've been in the same thing, basically giving a very delightful experience to both the segments, like the job, and so it's a marketplace, but it's a very technologically sophisticated marketplace where you don't show 10,000 jobs to a person and tell them to go and apply mass supply and they will only be relevant for 10 jobs and they will wait for like 10,000 replies. They will get only one to two replies and then they will be frustrated or demotivated.
Speaker 2:So yeah, yeah, again a very relevant problem that a lot of the space is when we are looking for a job, because we just go on random platforms and we would be literally being bombarded with job opportunities and then in all that mix we somehow miss on the opportunity which are actually relevant for us or which actually these are all time bound.
Speaker 3:Actually, what you said, this is all time bound, so you will not be hiring for a person for two years. You will be hiring for a person, say, if you find out within one and a half months, one month time, that will be good and you will start the process with this kind of candidates, right, or maybe in some very critical scenario, it will be seven days, yeah, okay, but if you, if you're wasting a lot of time finding out candidates like who to email who to communicate that that seven day or one month window is gone.
Speaker 2:Yeah.
Speaker 3:And so you're always lagging behind or always catching up. So that is one scenario which we have seen and the concept was to show earlier concept, before pre InstaHire era, it was to show maximum candidates per job so that everyone will be like, huh, I have a very good cushion of 10,000 candidates for my job and I have a huge pool of 10,000 candidates who will apply to my job. When you delve deeper into this, ideally there will be around 100, 150, 200 candidates, or maybe 500 candidates for some jobs who will be actually be relevant. But finding out this thing is very, very difficult, as you know. Like there will be like 10,000 resumes, 10,000 pieces of content which you need to manually go through not technically, like manually have to go through. So technologically, we have made it simpler so that you don't have to go through 10,000. You have to go only through people who are relevant. That is how it actually works. So that is how we have envisioned InstaHire. In the future, it will be only to get like, only to show opportunities which are which matter to you.
Speaker 2:Awesome. So, as I was reading that the InstaMatch technology is designed to mimic a human recruiter and you've already explained a lot about it, so is there, like any success story, where you realize that, okay, this is something that is actually going to work for us, or this would be like a breakthrough?
Speaker 3:So success stories. We have multiple companies example, like Salesforce, oracle. These are all companies. I've named a couple. We have like hundreds of success stories with us.
Speaker 3:So these companies, what they were doing earlier, is using the traditional methods. When they started using Insta, there was a wow factor and it has reduced their turnaround time, the tat, by 80%, 90%, increase their relevancy by 60%, 70%. So actually, when a recruiter of this company see a profile or post a job on InstaHire, versus other platforms, 70% of the candidates that they see are actually going up to the interview stage, versus 2 to 3% on other platforms. So that is where people are shifting to the product which gives you, say, I will give you only, say, 500 candidates, not 10th of the candidates, but all of this 500 candidates, 80, 90% will be relevant. They will move to the next stage. So your work is cut out right. So your work is basically to engage, to give them better experience.
Speaker 3:So how does a human recruiter actually do it? So what they do is they post a job and they see, say, suppose, an experienced recruiter who has like a 10 years experience. When he or she sees a profile, he will know that this is relevant for me or not relevant. They have to read through that profile so they will see certain key points experience, how the person has grown in his or her career, what are the projects he or she has done, what are the skills he or she has acquired during this and what are the type of companies they have worked for. So I've given you a few pointers. So if you make an engine which can identify these factors for you, so you don't need a human recruiter to find all this manually right and they will only see profiles which actually meets them, then what we have done is we have told the, we have given them the profiles. A recruiter can come and they can accept the candidate. So like to send them emails or they can reject it.
Speaker 3:I don't want it, so I'll go to the understand this and they will only show people who are very, very prone to getting an accept rather than a reject, so that the recruiter work is cut out. Also, the candidate work is also easier when you show candidates who can, like, are prone to getting an interview call, so that makes them pretty happy. So this is how we have been mimicking the human recruiter part of it. It's pretty difficult because, as you know, you cannot fully replace the human experience. So the human experience contains of two parts One is sourcing and one is engaging. So we have replaced the sourcing part of it, but the engaging part of it needs to be done by a recruiter because there will be certain nuances which the recruiter will understand how to talk to a candidate, how to sell a company, sell your vision, sell your USP so that all things is being done by the human part of it.
Speaker 2:I definitely do agree with the fact that I mean there has to be an automation of both. We leverage technology and yet human part is very important. So, talking about the future of recruitment, are there any upcoming features and developments that you look forward to to be brought on the platform?
Speaker 3:So the features which we have already brought is, as I told you, internships for the junior hiring. We are launching another tool, which is the application tracking system, which is which is very, very technologically sophisticated version of whatever tools we are right now seeing in the market, and it has also. It has also had to increase the number of accepts. Okay, so accepts mean the conversion ratios increase, because right now, our tool, our platform, was still the position where the recruiter talks to a candidate and that's it. That's where we left right now with the application tracking system.
Speaker 3:Okay, what we have done is this application tracking system, what you can to schedule interviews. You have automated reminders. So these automated reminders will be kind of when, say, I have emailed to you about a job and you are busy in office and I know exactly what time people will get free or like what times there will be a higher number of replies. So automated reminders will go and it will not look like a spam. It will be very, very so say hi, sir, you have been working in this company in the Python development and I had mailed you before but you could not have time. So, in a very human part of it, these are auto-generated neutral language emails, for also in diversity cases we have seen that there is a lot of very high reply backs because we generate these kind of emailers. We generate these kind of job description which are neutral in nature, which also helps the company's brand, and this is there. And ATS also helps in understanding what kind of candidates will make through actually to the later stages. And we feedback and we put really the feedback to the InstaMatch algorithm, which helps you to increase the chances of conversion. Okay, so there will be multiple series, as like in your company also. There will be multiple, such as there will be a telephonic internet, maybe an assignment. After that there will be one or two rounds of interview, right and the.
Speaker 3:When the technology sees, say, 10,000 interviews or 10,000 assignments and their submissions and rejections are accepted by the companies, it creates a model where it helps to suggest the InstaMatch algorithm, you should send this kind of candidates and this kind of candidates will convert.
Speaker 3:So this is how it actually works. It's like a intelligent system which tells cases like the interview results, what kind of candidates you should send. On the other hand, on the other part, it also helps the candidates. So when a candidate applies to a job, it shows a meter where it shows the candidate, there's a very high chance of you being converted because similar candidates like you have applied and had gone through the assignment stage. And in some cases it shows that there will be less chance, because of your profile and because of your previous work and all of this, that you might not get through or might not get a call, but still you can apply. And this is also can you also very clear, kiha? I have 15, 20, 100 jobs which I have very, very confident I will go through, and maybe another 100 jobs which I might be in a future scenario.
Speaker 2:So this is how we have done it. Awesome and I'm sure after this, especially listening to this podcast, a lot of people's problems would get solved via Insta hire. So thank you, Sir Bojit, for taking time out of your busy schedule and coming over for this podcast. Thank you so much.
Speaker 3:Thank you so much for having me. It was a pleasure talking to you.
Speaker 2:Likewise, and thanks to our listeners for tuning into this episode.